Tesseract [1]} is an open source for Optical Character Recognition that expects binary images and outputs a digital string of characters per input. First, Tesseract uses Adaptive Thresholding to binarize images, followed by Connected Component Analysis to find lines and words which are organized as units. Then, if a word is recognized, it aims at finding edges of characters that match their training set. Tesseract was originally trained using \(60\,160\)  samples of 94 characters, with 20 samples per class in 8 fonts and 4 presentations: normal, italic, bold, and bold-italic [1]}.
